Radial feature descriptors for cell classification and recommendation.

dc.contributor.authorSilva, Romuere Rodrigues Veloso e
dc.contributor.authorAraujo, Flavio Henrique Duarte de
dc.contributor.authorUshizima, Daniela Mayumi
dc.contributor.authorBianchi, Andrea Gomes Campos
dc.contributor.authorCarneiro, Cláudia Martins
dc.contributor.authorMedeiros, Fátima Nelsizeuma Sombra de
dc.date.accessioned2020-05-08T18:59:22Z
dc.date.available2020-05-08T18:59:22Z
dc.date.issued2019
dc.description.abstractThis paper introduces computational tools for cell classification into normal and abnormal, as well as content-based-image-retrieval (CBIR) for cell recommendation. It also proposes the radial feature descriptors (RFD), which define evenly interspaced segments around the nucleus, and proportional to the convexity of the nuclear boundary. Experiments consider Herlev and CRIC image databases as input to classification via Random Forest and bootstrap; we compare 14 different feature sets by means of False Negative Rate (FNR) and Kappa (k), obtaining FNR = 0.02 and k = 0.89 for Herlev, and FNR = 0.14 and k = 0.78 for CRIC. Next, we sort and rank cell images using convolutional neural networks and evaluate performance with the Mean Average Precision (MAP), achieving MAP = 0.84 and MAP = 0.82 for Herlev and CRIC, respectively. Cell classification show encouraging results regarding RFD, including its sensitivity to intensity variation around the nuclear membrane as it bypasses cytoplasm segmentation.pt_BR
dc.identifier.citationSILVA, R. R. V. et al. Radial feature descriptors for cell classification and recommendation. Journal of Visual Communication and Image Representation, v. 62, p. 105-116, jul. 2019. Disponível em: <https://www.sciencedirect.com/science/article/pii/S1047320319301452?via%3Dihub>. Acesso em: 10 fev. 2020.pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.jvcir.2019.04.012pt_BR
dc.identifier.issn1047-3203
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/12176
dc.identifier.uri2https://www.sciencedirect.com/science/article/pii/S1047320319301452?via%3Dihubpt_BR
dc.language.isoen_USpt_BR
dc.rightsrestritopt_BR
dc.subjectImage retrievalpt_BR
dc.subjectConvolutional neural networkspt_BR
dc.titleRadial feature descriptors for cell classification and recommendation.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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